Many users enter text into a plurality of devices. For example, a user may type text messages (SMS/MMS) or emails on a mobile phone in addition to writing emails or documents on a tablet or PC. Each of the devices comprises a text entry system to aid the user in their text entry.
The text entry system may comprise a language model which may be a probabilistic encapsulation of a given language style, e.g. a user's writing style. A language model based text entry system is capable of enhancing the typing experience on an electronic device through a range of functionality, e.g. correcting mistyped/misspelled input based on language and/or predicting likely future terms in a sequence.
The language model may be a dynamic language model, which is trained progressively on user input as the user enters text into the device, thus enabling the text entry system to correct mistyped/misspelled input or predict likely future terms in a sequence based on text previously entered by a user.
The inventors of the present application have identified a problem experienced by a user owning a plurality of devices, each of which learns the user's language style over time: the predictions generated by the devices can become divergent with use. For example, a user may use one device much more frequently that the other devices. The frequently used device will generate more accurate predictions for that user than the devices which are not often used, and this will be both annoying and problematic for the user.
It is an object of the invention to overcome such a problem.